Senior ML Engineer

Ambience HR LLP; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Ambience HR LLP in Bengaluru, across India, seeks an experienced AI/ML Engineer to deliver production-grade models, pipelines, and GenAI solutions. Strong Python/SQL skills and cloud deployment are essential for this role.

The candidate will work across Bangalore, Kochi, and Thiruvananthapuram, implementing MLOps, RAG workflows, and agentic AI with LangChain and related tools to drive real-world impact.

Qualifications

• 9–15 years of hands-on AI/ML experience in production.
• Strong Python and SQL proficiency.
• Experience in cloud-based deployment and monitoring.
• Proven ability to design and deploy GenAI/RAG solutions.

Responsibilities

• Develop and deploy production-grade AI/ML models beyond notebooks and PoCs.
• Build scalable ML pipelines using Python and complex SQL.
• Implement MLOps including Docker, APIs, CI/CD, deployment, monitoring, retraining, drift.
• Work with AWS, Azure, or GCP cloud platforms.
• Design and implement RAG pipelines and enterprise GenAI solutions.
• Develop agentic AI and tool-based workflows with LangChain, LangGraph, MCP, function calling, NL-to-SQL.
• Collaborate with engineering and business teams to integrate AI/ML into applications.
• Optimize models and pipelines for scalability and reliability.

Skills

Python

SQL

MLOps

Generative AI

RAG pipelines

Cloud computing

APIs

Docker

LangChain

Tools

AWS

Azure

GCP

LangChain

LangGraph

MCP

NL-to-SQL

Job description

We are looking for an experienced AI/ML Engineer with strong hands-on experience in production machine learning, MLOps, Generative AI, and RAG-based solutions. The ideal candidate should have strong Python and SQL skills and experience building, deploying, and monitoring AI/ML solutions in cloud environments.

Experience: 9-15 Years

Location: Bangalore,Kochi and Thiruvananthapuram

Employment Type: Full-Time

Key Responsibilities

• Develop and deploy production-grade AI/ML models beyond notebooks and PoCs.
• Build scalable ML pipelines using Python and complex SQL.
• Implement MLOps practices including Docker, APIs, CI/CD, model deployment, monitoring, retraining, and drift monitoring.
• Work with AWS, Azure, or GCP cloud platforms.
• Design and implement RAG pipelines and enterprise GenAI solutions.
• Develop agentic AI and tool-based workflows using technologies such as LangChain, LangGraph, MCP, function calling, or NL-to-SQL.
• Collaborate with engineering and business teams to integrate AI/ML solutions into real-world applications.
• Optimize models and pipelines for scalability, reliability, and performance